Results 51 to 60 of about 3,583,799 (330)
Functional Prediction of Hypothetical Proteins from and Validation of the Predicted Models by Using ROC Curve Analysis [PDF]
Genomics & Informatics, 2018 Shigella spp. constitutes some of the key pathogens responsible for the global burden of diarrhoeal disease. With over 164 million reported cases per annum, shigellosis accounts for 1.1 million deaths each year.
Md. Amran Gazi +9 more
doaj +1 more source
Nonparametric confidence intervals for the area under the ROC curve
Statistica, 2013 Following an idea by Jing et al. (2005), this paper combines the empirical likelihood for the mean functional with jackknife pseudo-values obtained from the Mann-Witney two-sample statistic.
Gianfranco Adimari
doaj +1 more source
ADC cut points for chronic kidney disease in pathologically-proven cholangiocarcinoma
European Journal of Radiology Open, 2021 Purpose: Apparent diffusion coefficient (ADC) has been shown to indicate renal function in various conditions. As cholangiocarcinoma may have renal involvement due to immune complex-mediated glomerulonephritis, this study aimed to determine whether or ...
Jaturat Kanpittaya +3 more
doaj +1 more source
ROC APP: AN APPLICATION TO UNDERSTAND ROC CURVES
Brazilian Journal of Biometrics, 2022 We present a software application (https://gfvonborries.shinyapps.io/roc_app/) to help students understand the Receiver Operating Characteristic (ROC) curve and other concepts associated with binary classification models. We use the diagnostic test scenario as a motivation to explain the underlying concepts and the app functionalities.
Georges Freitas VON BORRIES +1 more
openaire +1 more source
Relationship between Brier score and area under the binormal ROC curve [PDF]
, 2002 If we consider the Brier Score (B) in the context of the signal detection theory and assume that it makes sense to consider the existence of B as a parameter for the population (let B be this B), and if we assume that the calibration in the observer's ...
Ishigaki, Takeo +4 more
core +1 more source
Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve [PDF]
Neural Computation, 2016 The area under the ROC curve (AUC) is a widely used performance measure in machine learning. Increasingly, however, in several applications, ranging from ranking to biometric screening to medicine, performance is measured not in terms of the full area ...
H. Narasimhan, S. Agarwal
semanticscholar +1 more source
The genetic interpretation of area under the ROC curve in genomic profiling. [PDF]
PLoS Genetics, 2010 Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease.
Naomi R Wray +3 more
doaj +1 more source
Disease Markers, 2018 The detection of serum biomarkers can aid in the diagnosis of lung cancer. In recent years, an increasing number of lung cancer markers have been identified, and these markers have been reported to have varying diagnostic values.
Qixian Yang +4 more
semanticscholar +1 more source
Reasonably conduct the multiple Logistic regression analysis combined with the ROC curve analysis
Sichuan jingshen weisheng, 2022 The purpose of this paper was to introduce how to reasonably carry out the method of the multiple Logistic regression analysis by combining the ROC curve analysis. Firstly， it introduced two groups of the basic concepts related to the ROC curve analysis，
Hu Chunyan, Hu Liangping
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Is the ROC curve a reliable tool to compare the validity of landslide susceptibility maps?
, 2018 This study investigates how effective the receiver operating characteristic (ROC) curve is for comparing the reliability of landslide susceptibility maps (LSMs).
V. Vakhshoori, M. Zare
semanticscholar +1 more source